• 품질경영학회지
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• 제22권4호
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• pp.79-101
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• 1994

In modern manufacturing, a product consists of many components created by different processes. Variations in the individual component dimensions and in the processes may result in unacceptable final assemblies. Thus, engineers have increased pressure to properly set tolerance specifications for individual components and to control manufacturing processes. When a proper variation stack-up analysis is not performed for all of the components in a functional system, all component parts can be within specifications, but the final assembly may not be functional. Thus, in order to improve the performance of the final assembly, a proper variation stack-up analysis is essential for specifying dimensional tolerances and process control. This research provides a detailed case example of the use of variation stack-up analysis using a Monte Carlo simulation method to improve the defect rate of a complex process, which is the commutator brush track undercut process of an armature assembly of a small motor. Variations in individual component dimensions and process mean shifts cause high defect rate, Since some dimensional characteristics have non-normal distributions and the stack-up function is non-linear, the Monte Carlo simulation method is used.

• 산업경영시스템학회지
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• 제28권4호
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• pp.116-123
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• 2005

The traditional process capability indices Cp, Cpk, Cpm, $Cpm^+$ have been used to characterize process performance on the basis of univariate quality characteristics. Cp, Cpk consider the process variation, Cpm considers both the process variation and the process deviation from target and Cpm+ considers economic loss for the process deviation from target. In manufacturing industry, there is growing interest in quantitative measures of process variation under multivariate duality characteristics. The multivariate process capability index incorporates both the process variation and the process deviation from target or considers expected loss caused by the process deviation from target. This paper proposes multivariate capability index based on the expected loss derived from multivariate normal distribution.

• 한국물환경학회지
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• 제26권2호
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• pp.356-364
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• 2010

The chemical and biological reaction of the aquatic organism is closely related with temperature variation and water temperature is one of the most important factors that should be considered in establishing sustainable reservoir operation scheme to minimize adverse environmental impacts related with dam construction. This paper investigates temperature variation in the downstream of Yongdam Reservoir using sampled data collected from total 8 temperature monitoring stations placed along the main river and the major tributaries. Using KoRiv1, 1-dimensional dynamic water quality simulation model, temperature variation in the downstream of Yongdam Reservoir has been simulated. The simulated results were compared with sampled data collected from May 15 to August 1 2008 by applying two different temperature modeling schemes, equilibrium temperature and full heat budget method. From the result of statistical analysis, seasonal temperature variation has been simulated by applying the equilibrium temperature scheme for comparison of the difference between the reservoir operation and the natural conditions.

• 한국습지학회지
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• 제24권4호
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• pp.301-311
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• 2022

본 연구는 장기 수질모니터링 자료를 이용하여 수질의 계절적 특성을 분석하는 것이 목적이다. 낙동강수계에서 장기 모니터링이 수행되고 있는 34개 지류에서의 모니터링 자료를 이용하여 수질의 계절적 특성을 분석하였고 계절적 분석을 위해 수질의 평균 자료 분석과 변동계수(Coefficient of variation) 분석, 추세분석을 수행하였다. 변동계수 평가결과, 지류가 본류보다 크고 계절적으로는 BOD와 T-P, TOC는 가을철이 크고 T-N은 봄철이 크게 나타났다. 추세분석은 Mann-Kendall과 Sen's Slope를 통해 분석하였으며 BOD와 T-N, T-P는 감소 경향이 많으나 TOC는 증가 경향이 많았다. 또한, 공간적으로는 낙동강 상류보다 하류에서의 증가하는 경향이 많이 나타났다. 본 연구를 통해 장기 수질모니터링 자료의 활용성 평가 및 계절적 특성을 분석할 수 있었고 유역관리를 위해 수질의 안정화 시기, 오염원 증감 변화를 분석할 수 있었다.

• 한국환경보건학회지
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• 제27권3호
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• pp.35-42
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• 2001

The characteristics of water quality variation were predicted by stochastic model in Chungju dam, north Chungcheong province of south Korea, Monthly time series data of water quality from 1989 to 2001;temperature, BOD, COD and SS, were obtained from environmental yearbook and internet homepage of ministry of environment. Development of model was carried out with Box-Jenkins method, which includes model identification, estimation and diagnostic checking. ACF and PACF were used to model identification. AIC and BIC were used to model estimation. Seosonal multiplicative ARIMA(1, 0, 1)(1, 1, 0)$_{12}$ model was appropriate to explain stochastic characteristics of temperature. BOD model was ARMa(2, 2, 1), COD was seasonal multiplicative ARIMA(2. 0. 1)(1. 0, 1)$_{12}$, and SS was ARIMA(1, 0, 2) respectively. The simulated water quality data showed a good fitness to the observed data, as a result of model verification.ion.

• 전기학회논문지
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• 제57권11호
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• pp.1946-1953
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• 2008

Power system of Jeju is interconnected to the mainland using HVDC and that is also interconnected to three wind farms. It will be difficult to control of Jeju power system if HVDC is disconnected or HVDC is overhauled under large scale wind farms interconnected. We measured and analysed the power quality of two substation and two wind farms to assess that wind farms have an effect on Jeju system during the HVDC overhaul last May. We concentrated on the power quality like frequency, voltage variation, voltage harmonics, current harmonics, flicker. We can found that the frequency of Jeju system is very unstable during overhaul, so the frequency of Jeju system can be variated easily by wind farm's rapid output power variation. There are some benefits and weak points in power quality between two wind farms because each wind farm is consist of different wind turbines.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2005년도 춘계학술대회
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• pp.503-521
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• 2005

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for muliple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index $MC_{pm}^{++}$ using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other,

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2004년도 추계학술대회
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• pp.69-79
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• 2004

Process capability indices are widely used in industries and quality assurance system. When designing the parameter on the multiple quality characteristics, there has been a study for optimization of problems, but there has been few former study on the possible conflicting phenomena in considertion of the correlations among the characteristics. To solve the issue on the optimal design for multiple quality characteristics, the study propose the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of terms. Therefore, the analysis have to be required a multivariate statistical technique. This paper introduces to multivariate capability indices and then selects a multivariate process capability index incorporated both the process variation and the process deviation from target among these indices under the multivariate normal distribution. We propose a new multivariate capability index $MC_{pm}^{++}$ using quality loss function instead of the process variation and this index is compared with the proposed indices when quality characteristics are independent and dependent of each other.

• 통합자연과학논문집
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• 제6권1호
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• pp.39-45
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• 2013

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Taguchi has an idea that mean and variation are handled simultaneously to reduce the expected loss in products and processes. In the Taguchi parameter design, the product-array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined-array approach, was studied. In these studies, only single quality characteristic (or response) was considered. In this paper we propose how to simultaneously optimize for multiple quality characteristics (or multiresponse) using desirability function when we used the combined-array approach to assign control and noise factors.

• 산업경영시스템학회지
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• 제26권1호
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• pp.7-16
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• 2003

At present, company has to produce a product that consumer like with a competitive price, a good quality, and a fitting time to supply. Process control and quality control are very important to supply with a product uniformly and inexpensively. Process control is given much weight in the quality control in manufacturing system. Statistical process controls(SPC) that are used in process generally have major impact on manufacturing, product design activities, and process development potentially. Control charts in statistical process control method can be interpreted the data from quality characteristics in production process and discriminated between chance variation and assignable variation in process. In addition, control chart can be used to monitor the process output and detect when changes in the inputs are required to bring the process back to an in-control state. The models that relate the influential inputs to process outputs help determine the nature and magnitude of the adjustments required. In this paper, the characteristic of product quality is monitored by control chart during the machining process and construction of quality control cycle is considered to divide into two types in this case that different assignable causes lead to shifts having different magnitudes. Then we are intended to find a process shift magnitude which has economical quality cost policy and are considered to quality cost functions to find a process shift magnitude. Those costs are categorized into the well-known categories of prevention, appraisal, and internal failure and external failure. This paper ends with numerical examples that demonstrate the usefulness of the model.